Race to Recovery: Designing Advanced Safety Systems for Autonomous Driving via Learning Autonomous Racing
The research developed a method to improve vehicle control after a loss of control by transferring skills learned from racing. Instead of training recovery systems directly, they first trained an AI policy to race while drifting, then adapted that policy for recovery. This transfer learning approach significantly outperformed existing recovery methods and classical controllers in recovering vehicles from difficult states.